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This is a medium difficulty Coding & Algorithms question, commonly asked during Technical Screen rounds at Bytedance.

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This question is commonly asked for Data Scientist candidates at Bytedance during technical interviews.

Count Same-Day Registered Posters | Bytedance Coding Question

Quick Overview

This question evaluates SQL querying skills, including joining relational tables, date handling, aggregation, and deduplicating users across events. Commonly asked in Coding & Algorithms interviews for data scientists, it assesses practical relational database querying and analytics tasks—filtering, grouping, and counting distinct users across tables—and tests practical application of SQL rather than purely conceptual database theory; this summary is in English.

Count Same-Day Registered Posters

Company: Bytedance

Role: Data Scientist

Category: Coding & Algorithms

Difficulty: medium

Interview Round: Technical Screen

You are given two tables: ```text users - user_id: unique identifier for a user - registered_at: timestamp when the user registered posts - post_id: unique identifier for a post - user_id: identifier of the user who published the post - created_at: timestamp when the post was published ``` Write a SQL query that returns, for each calendar date, the number of distinct users who registered on that date and also published at least one post on that same date. Important detail: a user may publish multiple posts on the same day, but that user should be counted only once for that date. Expected output: ```text registration_date | user_count ```

Quick Answer: This question evaluates SQL querying skills, including joining relational tables, date handling, aggregation, and deduplicating users across events. Commonly asked in Coding & Algorithms interviews for data scientists, it assesses practical relational database querying and analytics tasks—filtering, grouping, and counting distinct users across tables—and tests practical application of SQL rather than purely conceptual database theory; this summary is in English.

You are given two tables, `users` and `posts`. - `users(user_id, registered_at)` stores when each user registered. - `posts(post_id, user_id, created_at)` stores when each post was published. For each calendar date, count how many distinct users both: 1. registered on that date, and 2. published at least one post on that same date. If a user publishes multiple posts on the same day, they must be counted only once for that date. Return the result sorted by `registration_date` in ascending order. Dates with no qualifying users should not appear. Note: The original interview version is a SQL problem. In this coding version, the two tables are provided as Python lists of tuples, and each timestamp is a string in `YYYY-MM-DD HH:MM:SS` format.

Constraints

0 <= len(users), len(posts) <= 200000
Each `user_id` in `users` is unique
Timestamps are valid strings in `YYYY-MM-DD HH:MM:SS` format
A user may publish multiple posts on the same day, but counts only once for that date
Posts whose `user_id` does not exist in `users` should be ignored

Examples

Input: ([(1, "2023-07-01 08:00:00"), (2, "2023-07-01 09:30:00"), (3, "2023-07-02 10:00:00")], [(10, 1, "2023-07-01 12:00:00"), (11, 1, "2023-07-01 13:00:00"), (12, 2, "2023-07-02 08:00:00"), (13, 3, "2023-07-02 11:00:00"), (14, 2, "2023-07-01 18:00:00")])

Expected Output: [("2023-07-01", 2), ("2023-07-02", 1)]

Explanation: Users 1 and 2 both registered and posted on 2023-07-01. User 1 posted twice but is counted once. User 3 qualifies on 2023-07-02.

Input: ([(1, "2023-01-01 00:00:00"), (2, "2023-01-01 05:00:00"), (3, "2023-01-03 09:00:00"), (4, "2023-01-03 11:00:00")], [(1, 1, "2023-01-01 10:00:00"), (2, 2, "2023-01-02 10:00:00"), (3, 3, "2023-01-03 09:30:00"), (4, 3, "2023-01-03 10:00:00"), (5, 5, "2023-01-03 12:00:00")])

Expected Output: [("2023-01-01", 1), ("2023-01-03", 1)]

Explanation: User 1 qualifies on 2023-01-01. User 3 qualifies on 2023-01-03 and is counted once despite two posts. User 2 posted on a different day, user 4 never posted, and user 5 does not exist in users.

Input: ([], [])

Expected Output: []

Explanation: With no users and no posts, there are no qualifying dates.

Input: ([(1, "2024-02-29 23:59:59")], [(1, 1, "2024-03-01 00:00:00")])

Expected Output: []

Explanation: The user posted, but not on the same calendar date as registration.

Input: ([(7, "2022-12-31 00:00:00")], [(100, 7, "2022-12-31 01:00:00"), (101, 7, "2022-12-31 23:00:00")])

Expected Output: [("2022-12-31", 1)]

Explanation: The same user made multiple posts on the registration day, but should only be counted once.

Hints

Extract the date part from both timestamps before comparing them.
To avoid counting multiple posts from the same user on the same day more than once, store matched users in a set before aggregating.

Last updated: May 12, 2026

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Quick Overview

Count Same-Day Registered Posters

Company: Bytedance

Role: Data Scientist

Category: Coding & Algorithms

Difficulty: medium

Interview Round: Technical Screen

Constraints

0 <= len(users), len(posts) <= 200000
Each `user_id` in `users` is unique
Timestamps are valid strings in `YYYY-MM-DD HH:MM:SS` format
A user may publish multiple posts on the same day, but counts only once for that date
Posts whose `user_id` does not exist in `users` should be ignored

Examples

Expected Output: [("2023-07-01", 2), ("2023-07-02", 1)]

Explanation: Users 1 and 2 both registered and posted on 2023-07-01. User 1 posted twice but is counted once. User 3 qualifies on 2023-07-02.

Expected Output: [("2023-01-01", 1), ("2023-01-03", 1)]

Input: ([], [])

Expected Output: []

Explanation: With no users and no posts, there are no qualifying dates.

Input: ([(1, "2024-02-29 23:59:59")], [(1, 1, "2024-03-01 00:00:00")])

Expected Output: []

Explanation: The user posted, but not on the same calendar date as registration.

Input: ([(7, "2022-12-31 00:00:00")], [(100, 7, "2022-12-31 01:00:00"), (101, 7, "2022-12-31 23:00:00")])

Expected Output: [("2022-12-31", 1)]

Explanation: The same user made multiple posts on the registration day, but should only be counted once.

Hints

Extract the date part from both timestamps before comparing them.
To avoid counting multiple posts from the same user on the same day more than once, store matched users in a set before aggregating.

Last updated: May 12, 2026

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